README.md
In yutannihilation/tiedr: Experimental Package For Multi-Gather And Multi-Spread
tiedr
tiedr is an experimental package to “pack” (or “bundle”) some columns to
a data.frame column.
The idea behind this package is basically the same as
pack()/unpack(), which was proposed on the tidyr’s issue below. I
didn’t notice this issue at the time of deciding the main function name
as bundle()…
If you wonder how this is useful, my blog post might
help:
Usages
bundle() and unbundle()
bundle() packs columns into a data.frame column, and unbundle()
unpacks it.
library(tiedr)
iris <- tibble::as_tibble(iris)
# bundle() takes unnamed arguments
iris %>%
bundle(-Species)
#> # A tibble: 150 x 2
#> data$Sepal.Length $Sepal.Width $Petal.Length $Petal.Width Species
#> <dbl> <dbl> <dbl> <dbl> <fct>
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3 1.4 0.2 setosa
#> 3 4.7 3.2 1.3 0.2 setosa
#> 4 4.6 3.1 1.5 0.2 setosa
#> 5 5 3.6 1.4 0.2 setosa
#> 6 5.4 3.9 1.7 0.4 setosa
#> 7 4.6 3.4 1.4 0.3 setosa
#> 8 5 3.4 1.5 0.2 setosa
#> 9 4.4 2.9 1.4 0.2 setosa
#> 10 4.9 3.1 1.5 0.1 setosa
#> # ... with 140 more rows
# bundle() also takes named arguments
d <- iris %>%
bundle(Sepal = starts_with("Sepal"),
Petal = starts_with("Petal"))
# bundled columns can be bundled
d %>%
bundle(-Species)
#> # A tibble: 150 x 2
#> data$Sepal$Sepal.L~ $$Sepal.Width $Petal$Petal.Le~ $$Petal.Width Species
#> <dbl> <dbl> <dbl> <dbl> <fct>
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3 1.4 0.2 setosa
#> 3 4.7 3.2 1.3 0.2 setosa
#> 4 4.6 3.1 1.5 0.2 setosa
#> 5 5 3.6 1.4 0.2 setosa
#> 6 5.4 3.9 1.7 0.4 setosa
#> 7 4.6 3.4 1.4 0.3 setosa
#> 8 5 3.4 1.5 0.2 setosa
#> 9 4.4 2.9 1.4 0.2 setosa
#> 10 4.9 3.1 1.5 0.1 setosa
#> # ... with 140 more rows
# unbundle()
unbundle(d, Sepal, Petal, sep = NULL)
#> # A tibble: 150 x 5
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> <dbl> <dbl> <dbl> <dbl> <fct>
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3 1.4 0.2 setosa
#> 3 4.7 3.2 1.3 0.2 setosa
#> 4 4.6 3.1 1.5 0.2 setosa
#> 5 5 3.6 1.4 0.2 setosa
#> 6 5.4 3.9 1.7 0.4 setosa
#> 7 4.6 3.4 1.4 0.3 setosa
#> 8 5 3.4 1.5 0.2 setosa
#> 9 4.4 2.9 1.4 0.2 setosa
#> 10 4.9 3.1 1.5 0.1 setosa
#> # ... with 140 more rows
auto_bundle()
d <- tibble::tribble(
~A_a_x, ~A_a_y, ~A_b_x, ~B_a_x, ~B_b_x, ~B_b_y,
1, 2, 3, 4, 5, 6,
2, 3, 4, 5, 6, 7
)
auto_bundle(d, everything())
#> # A tibble: 2 x 2
#> A$a$x $$y $b$x B$a$x $b$x $$y
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 3 4 5 6
#> 2 2 3 4 5 6 7
auto_bundle(d, starts_with("A"))
#> # A tibble: 2 x 4
#> A$a$x $$y $b$x B_a_x B_b_x B_b_y
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 3 4 5 6
#> 2 2 3 4 5 6 7
gather_bundles()
auto_bundle(d, everything()) %>%
gather_bundles()
#> # A tibble: 4 x 3
#> key a$x $y b$x $y
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 A 1 2 3 NA
#> 2 A 2 3 4 NA
#> 3 B 4 NA 5 6
#> 4 B 5 NA 6 7
auto_bundle(d, everything()) %>%
gather_bundles(.key = "key_outer") %>%
gather_bundles(.key = "key_inner")
#> # A tibble: 8 x 4
#> key_outer key_inner x y
#> <chr> <chr> <dbl> <dbl>
#> 1 A a 1 2
#> 2 A a 2 3
#> 3 B a 4 NA
#> 4 B a 5 NA
#> 5 A b 3 NA
#> 6 A b 4 NA
#> 7 B b 5 6
#> 8 B b 6 7
auto_bundle(d, everything()) %>%
gather_bundles(.key = "key_outer") %>%
gather_bundles(.key = "key_inner") %>%
gather_bundles(x:y, .key = "xy")
#> # A tibble: 16 x 4
#> key_outer key_inner xy value
#> <chr> <chr> <chr> <dbl>
#> 1 A a x 1
#> 2 A a x 2
#> 3 B a x 4
#> 4 B a x 5
#> 5 A b x 3
#> 6 A b x 4
#> 7 B b x 5
#> 8 B b x 6
#> 9 A a y 2
#> 10 A a y 3
#> 11 B a y NA
#> 12 B a y NA
#> 13 A b y NA
#> 14 A b y NA
#> 15 B b y 6
#> 16 B b y 7
spread_bundles()
# https://github.com/tidyverse/tidyr/issues/149
d <- tibble::tribble(
~hw, ~name, ~mark, ~pr,
"hw1", "anna", 95, "ok",
"hw1", "alan", 90, "meh",
"hw1", "carl", 85, "ok",
"hw2", "alan", 70, "meh",
"hw2", "carl", 80, "ok"
)
spread_bundles(d, name, c(mark, pr))
#> # A tibble: 2 x 4
#> hw alan$mark $pr anna$mark $pr carl$mark $pr
#> <chr> <dbl> <chr> <dbl> <chr> <dbl> <chr>
#> 1 hw1 90 meh 95 ok 85 ok
#> 2 hw2 70 meh NA <NA> 80 ok
spread_bundles(d, name, c(mark, pr)) %>%
unbundle(-hw)
#> # A tibble: 2 x 7
#> hw alan_mark alan_pr anna_mark anna_pr carl_mark carl_pr
#> <chr> <dbl> <chr> <dbl> <chr> <dbl> <chr>
#> 1 hw1 90 meh 95 ok 85 ok
#> 2 hw2 70 meh NA <NA> 80 ok
# without prefix
spread_bundles(d, name, c(mark, pr)) %>%
unbundle(-hw, sep = NULL)
#> # A tibble: 2 x 7
#> hw mark pr mark pr mark pr
#> <chr> <dbl> <chr> <dbl> <chr> <dbl> <chr>
#> 1 hw1 85 ok 85 ok 85 ok
#> 2 hw2 80 ok 80 ok 80 ok
# ?spread
tibble::tibble(x = c("a", "b"), y = c(3, 4), z = c(5, 6)) %>%
spread_bundles(x, y)
#> # A tibble: 2 x 3
#> z a b
#> <dbl> <dbl> <dbl>
#> 1 5 3 NA
#> 2 6 NA 4
yutannihilation/tiedr documentation built on May 28, 2019, 9:54 p.m.
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
tiedr
tiedr is an experimental package to “pack” (or “bundle”) some columns to a data.frame column.
The idea behind this package is basically the same as
pack()/unpack(), which was proposed on the tidyr’s issue below. I
didn’t notice this issue at the time of deciding the main function name
as bundle()…
If you wonder how this is useful, my blog post might help:
Usages
bundle() and unbundle()
bundle() packs columns into a data.frame column, and unbundle()
unpacks it.
library(tiedr)
iris <- tibble::as_tibble(iris)
# bundle() takes unnamed arguments
iris %>%
bundle(-Species)
#> # A tibble: 150 x 2
#> data$Sepal.Length $Sepal.Width $Petal.Length $Petal.Width Species
#> <dbl> <dbl> <dbl> <dbl> <fct>
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3 1.4 0.2 setosa
#> 3 4.7 3.2 1.3 0.2 setosa
#> 4 4.6 3.1 1.5 0.2 setosa
#> 5 5 3.6 1.4 0.2 setosa
#> 6 5.4 3.9 1.7 0.4 setosa
#> 7 4.6 3.4 1.4 0.3 setosa
#> 8 5 3.4 1.5 0.2 setosa
#> 9 4.4 2.9 1.4 0.2 setosa
#> 10 4.9 3.1 1.5 0.1 setosa
#> # ... with 140 more rows
# bundle() also takes named arguments
d <- iris %>%
bundle(Sepal = starts_with("Sepal"),
Petal = starts_with("Petal"))
# bundled columns can be bundled
d %>%
bundle(-Species)
#> # A tibble: 150 x 2
#> data$Sepal$Sepal.L~ $$Sepal.Width $Petal$Petal.Le~ $$Petal.Width Species
#> <dbl> <dbl> <dbl> <dbl> <fct>
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3 1.4 0.2 setosa
#> 3 4.7 3.2 1.3 0.2 setosa
#> 4 4.6 3.1 1.5 0.2 setosa
#> 5 5 3.6 1.4 0.2 setosa
#> 6 5.4 3.9 1.7 0.4 setosa
#> 7 4.6 3.4 1.4 0.3 setosa
#> 8 5 3.4 1.5 0.2 setosa
#> 9 4.4 2.9 1.4 0.2 setosa
#> 10 4.9 3.1 1.5 0.1 setosa
#> # ... with 140 more rows
# unbundle()
unbundle(d, Sepal, Petal, sep = NULL)
#> # A tibble: 150 x 5
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> <dbl> <dbl> <dbl> <dbl> <fct>
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3 1.4 0.2 setosa
#> 3 4.7 3.2 1.3 0.2 setosa
#> 4 4.6 3.1 1.5 0.2 setosa
#> 5 5 3.6 1.4 0.2 setosa
#> 6 5.4 3.9 1.7 0.4 setosa
#> 7 4.6 3.4 1.4 0.3 setosa
#> 8 5 3.4 1.5 0.2 setosa
#> 9 4.4 2.9 1.4 0.2 setosa
#> 10 4.9 3.1 1.5 0.1 setosa
#> # ... with 140 more rows
auto_bundle()
d <- tibble::tribble(
~A_a_x, ~A_a_y, ~A_b_x, ~B_a_x, ~B_b_x, ~B_b_y,
1, 2, 3, 4, 5, 6,
2, 3, 4, 5, 6, 7
)
auto_bundle(d, everything())
#> # A tibble: 2 x 2
#> A$a$x $$y $b$x B$a$x $b$x $$y
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 3 4 5 6
#> 2 2 3 4 5 6 7
auto_bundle(d, starts_with("A"))
#> # A tibble: 2 x 4
#> A$a$x $$y $b$x B_a_x B_b_x B_b_y
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 3 4 5 6
#> 2 2 3 4 5 6 7
gather_bundles()
auto_bundle(d, everything()) %>%
gather_bundles()
#> # A tibble: 4 x 3
#> key a$x $y b$x $y
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 A 1 2 3 NA
#> 2 A 2 3 4 NA
#> 3 B 4 NA 5 6
#> 4 B 5 NA 6 7
auto_bundle(d, everything()) %>%
gather_bundles(.key = "key_outer") %>%
gather_bundles(.key = "key_inner")
#> # A tibble: 8 x 4
#> key_outer key_inner x y
#> <chr> <chr> <dbl> <dbl>
#> 1 A a 1 2
#> 2 A a 2 3
#> 3 B a 4 NA
#> 4 B a 5 NA
#> 5 A b 3 NA
#> 6 A b 4 NA
#> 7 B b 5 6
#> 8 B b 6 7
auto_bundle(d, everything()) %>%
gather_bundles(.key = "key_outer") %>%
gather_bundles(.key = "key_inner") %>%
gather_bundles(x:y, .key = "xy")
#> # A tibble: 16 x 4
#> key_outer key_inner xy value
#> <chr> <chr> <chr> <dbl>
#> 1 A a x 1
#> 2 A a x 2
#> 3 B a x 4
#> 4 B a x 5
#> 5 A b x 3
#> 6 A b x 4
#> 7 B b x 5
#> 8 B b x 6
#> 9 A a y 2
#> 10 A a y 3
#> 11 B a y NA
#> 12 B a y NA
#> 13 A b y NA
#> 14 A b y NA
#> 15 B b y 6
#> 16 B b y 7
spread_bundles()
# https://github.com/tidyverse/tidyr/issues/149
d <- tibble::tribble(
~hw, ~name, ~mark, ~pr,
"hw1", "anna", 95, "ok",
"hw1", "alan", 90, "meh",
"hw1", "carl", 85, "ok",
"hw2", "alan", 70, "meh",
"hw2", "carl", 80, "ok"
)
spread_bundles(d, name, c(mark, pr))
#> # A tibble: 2 x 4
#> hw alan$mark $pr anna$mark $pr carl$mark $pr
#> <chr> <dbl> <chr> <dbl> <chr> <dbl> <chr>
#> 1 hw1 90 meh 95 ok 85 ok
#> 2 hw2 70 meh NA <NA> 80 ok
spread_bundles(d, name, c(mark, pr)) %>%
unbundle(-hw)
#> # A tibble: 2 x 7
#> hw alan_mark alan_pr anna_mark anna_pr carl_mark carl_pr
#> <chr> <dbl> <chr> <dbl> <chr> <dbl> <chr>
#> 1 hw1 90 meh 95 ok 85 ok
#> 2 hw2 70 meh NA <NA> 80 ok
# without prefix
spread_bundles(d, name, c(mark, pr)) %>%
unbundle(-hw, sep = NULL)
#> # A tibble: 2 x 7
#> hw mark pr mark pr mark pr
#> <chr> <dbl> <chr> <dbl> <chr> <dbl> <chr>
#> 1 hw1 85 ok 85 ok 85 ok
#> 2 hw2 80 ok 80 ok 80 ok
# ?spread
tibble::tibble(x = c("a", "b"), y = c(3, 4), z = c(5, 6)) %>%
spread_bundles(x, y)
#> # A tibble: 2 x 3
#> z a b
#> <dbl> <dbl> <dbl>
#> 1 5 3 NA
#> 2 6 NA 4
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